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Cornell University
- Ithaca, NY
- http://www.cs.cornell.edu/~junwen/
- https://scholar.google.com/citations?user=JD7wLV4AAAAJ&hl=en
- in/junwen-bai-7ba354155
Stars
[NeurIPS 2024] Official Repository of The Mamba in the Llama: Distilling and Accelerating Hybrid Models
clone/download repositories from https://anonymous.4open.science/
Layer-wise analysis of self-supervised pre-trained speech representations
Refine high-quality datasets and visual AI models
Grokking the System Design Interview Course
Official Repository of Pretraining Without Attention (BiGS), BiGS is the first model to achieve BERT-level transfer learning on the GLUE benchmark with subquadratic complexity in length (or without…
https://tuixue.online/visa/ A Real-time Display of U.S. Visa Appointment Status Website 预约美帝签证各个签证处最早时间的爬虫
A GNN-RNN approach for harnessing geospatial and temporal information: application to crop yield prediction
Attention-based Crystal to Sequence Learning for Density of States Prediction
Code for paper "Monitoring Vegetation at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net" (IJCAI 2022)
[ACL 2022] Structured Pruning Learns Compact and Accurate Models https://arxiv.org/abs/2204.00408
Implementation of https://srush.github.io/annotated-s4
mingzhong15 / deepmd-kit
Forked from deepmodeling/deepmd-kitA deep learning package for many-body potential energy representation and molecular dynamics
C-GMVAE: Gaussian Mixture VAE with Contrastive Learning for Multi-Label Classification
An annotated implementation of the Transformer paper.
JunwenBai / ASL
Forked from Alibaba-MIIL/ASLOfficial Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(ICCV, 2021) paper
Contrastively Disentangled Sequential Variational Audoencoder
Sprites video data used in the ICML 2018 paper
The repo collects all the coding assignments from ORIE 6700 at Cornell.
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Taming Transformers for High-Resolution Image Synthesis
This repository contains codes for the paper entitled "A CNN-RNN Framework for Crop Yield Prediction"